Effective coverage and budget implications of skill-mix change to improve neonatal nursing care: an explorative simulation study in Kenya.

INTRODUCTION: Neonatal mortality is an urgent policy priority to improve global population health and reduce health inequality. As health systems in Kenya and elsewhere seek to tackle increased neonatal mortality by improving the quality of care, one option is to train and employ neonatal healthcare assistants (NHCAs) to support professional nurses by taking up low-skill tasks. METHODS: Monte-Carlo simulation was performed to estimate the potential impact of introducing NHCAs in neonatal nursing care in four public hospitals in Nairobi on effectively treated newborns and staff costs over a period of 10 years. The simulation was informed by data from 3 workshops with >10 stakeholders each, hospital records and scientific literature. Two univariate sensitivity analyses were performed to further address uncertainty. RESULTS: Stakeholders perceived that 49% of a nurse full-time equivalent could be safely delegated to NHCAs in standard care, 31% in intermediate care and 20% in intensive care. A skill-mix with nurses and NHCAs would require ~2.6 billionKenyan Shillings (KES) (US$26 million) to provide quality care to 58% of all newborns in need (ie, current level of coverage in Nairobi) over a period of 10 years. This skill-mix configuration would require ~6 billion KES (US$61 million) to provide quality of care to almost all newborns in need over 10 years. CONCLUSION: Changing skill-mix in hospital care by introducing NHCAs may be an affordable way to reduce neonatal mortality in low/middle-income countries. This option should be considered in ongoing policy discussions and supported by further evidence.